Modeling of the impacts of monetary and fiscal policy in the Russian economy with GE-IO model of Russia with aggregated money and currency markets*

Transcription

1 Modeling of the impacts of monetary and fiscal policy in the Russian economy with GE-IO model of Russia with aggregated money and currency markets* Vadim Gilmundinov Novosibirsk National Research State University** Institute of Economics and Industrial Engineering SB of RAS Novosibirsk State Technical University Novosibirsk, Russia * The study is supported by the Russian Fund of Humanities in framework of scientific project Influence of Macroeconomic Policy with Monetary and Currency Restrictions on Dynamics and Structure of a Raw-Export Oriented National Economy with Imperfect Markets, a project ** The paper is presented at the 22 nd INFORUM World Conference (Alexandria, VA, USA, August 30 September 6, 2014) with cofinancing of Novosibirsk National Research State University in framework of the Program of Increasing Competitiveness «Top5-100». Key words: inflation targeting, money supply, monetary policy, fiscal policy, general equilibrium, macroeconometrics, input-output model, economic forecast 0. Introduction Gradual exhaustion of raw-export model of economic development in Russia (see, for example, (Baranov, 2013)) imposes new requirements to government economic policy as well as new demands on comprehensive study, estimation and scientific substantiation of new alternative models of the Russian economy s development, which could replace existing one, to the Economics. The extension of economic models constructed for the Russian economy and applied to estimate consequences of different scenarios of economic development is one of the important issues of scientific substantiation of an economic development model and relative priorities in economic policy. In this regard the issues of extension of dynamic input-output models which allow detailed simulating economic dynamics and branch structure acquire a special role. However most of soviet-time input-output models of the Russian economy have a well-known restriction for applying them to simulate market interrelations and finance flows between sectors and branches of national economy. The extension of dynamic input-output models to consider resource restrictions, mainly sectors finance restrictions, is another issue for research. For this purposes, in this paper we present a concept of extension of macroeconometric general equilibrium input-output model of the Russian economy with aggregated money and currency markets 1. The extension allows to consider macroeconomic and intersectoral relations influenced by monetary and fiscal shocks. Key equations, empirical estimations and applications of this model are also presented in the paper. 1. Macroeconometric GE-IO model of the Russian economy with aggregated markets 1 A basic version of this model is described in (Gilmundinov, 2012). 1

2 A basic version of the macroeconometric general equilibrium input-output model of the Russian economy with aggregated money and currency markets is described in (Gilmundinov, 2012). The extension of the model is based on combining of macroeconometric input-output approach suggested by C. Almon (Almon, 1989), computable general equilibrium approach suggested by L. Johansen (Johansen, 1974) and neo-classic and neo-keynesians macroeconomic models used to describe aggregated markets (see, for example, (Gali, 2008)). Theoretical concept of the extension of the macroeconometric general equilibrium inputoutput model of the Russian economy with aggregated money and currency markets is shown on Scheme 1. The model includes IO equations for product markets with input-output coefficients to simulate inter-sectoral relations, as well as econometrically estimated equations for aggregated monetary and currency markets and sectors output elasticities to simulate an inter-sectoral competition and links between aggregated markets. Currency market (macroeconometric model) x, P, Exp, Imp ER M, R x, P, r, K x, P Labor market Goods and service markets (macroeconometric GE-IO model) L, w (multi-sectoral econometric model) ER M, R I Money market (macroeconometric model) G, TR, Sub Tax, DivG GDin State budget x, P, r, K PBGI GI Capital market (multi-sectoral econometric model) GDout M, R Exp - vector of volumes of export; Imp - vector of volumes of import; ER - nominal exchange rate; M - nominal money supply; R - interest rate; r - vector of profitability; K - vector of volumes of fixed capital; L - vector of volumes of employed; w - vector of wages; I - vector of capital investments; GDin - cash flows related with increase of state debt; GDout - cash flows related with decrease of state debt and interest payments; G - vector of volumes of government purchases; TR - government transfers to householders; Sub - vector of volumes of government subsidies to producers; Tax - vector of volumes of taxes; DivG - incomes from state property; GI - vector of volumes of government investments PBGI - incomes from selling state property. Scheme 1. A Concept of macroeconometric GE-IO model with aggregated money and currency markets and shocks of monetary and fiscal policy A core of the model is an macroeconometric GE-IO model with 28 sectors in the current version (see equations (1) below). The GE-IO model simulates volumes of total outputs for each sector of economy based on simulating of total demand (see equations (2) below) and production capacities (see equations (3) below). Total demand and capacity constraints are based on inward and backward links with macroeconometric models, which describes aggregated markets. (only money and currency markets in the current version). Links between GE-IO model and macroeconometric models of aggregated markets are based on the endogenization of some key variables of aggregated markets which have influence on sectoral outputs (interest rate, exchange rate, inflation rates). In the current version of the model we assume only three variables of aggregated markets linked with total demand (real exchange rate, real wage, and real interest rate). 2

3 n x i, t = ai, j x j, t + yi, t j= 1 i = 1,,n (1) (2) Ln( x / x ) = e Ln( ExR$ R $ / ExR$ R $ + e i, t x, WR i i, t 4 Ln( WR t τ x, ExR$ R i WR xi / WR t τ WR xi 4 ) + e t τ x, IRR i ExR xi R Ln(1 + IRR t τ t τ ExR xi IRR xi R 4 ) + ) + e 0 i i = 1,,n (3) x i t Capi, t, i = 1,,n where n number of sectors (n = 28 in the current version); x, volume of total demand for product of sector i in quarter t in constant prices; i t y, volume of final demand for product of sector i in quarter t in constant prices; i t a i,j coefficients of direct expenditures of sector j for products of sector i, i, j = 1,, n; ExR$ R WR IRR τ x i, τ x i, τ x i time lags in influence of changing in real exchange rate, real wage, and real interest rate on total demand for product of sector i estimated by constructing regression equations; ExR $ $ R t τ ExR R real exchange rate of the Russian ruble to US dollar in quarter x i t ExR$ R τ ; x i WRt τ WR x i real wage in quarter WR t τ xi ; IRR IRR t τ xi average annual real interest rate (deflated with deflator of GDP) for credits for nonfinancial sector in quarter IRR t τ xi ; e x i, ExR$ R, e x i, WR, e x i, IRR elasticity coefficients of total demand for product of sector i to real exchange rate, real wage, and real interest rate, accordingly, estimated by constructing regression equations (see Table 1); 0 e i a constant term of regression equation for total demand for product of sector i; Cap, production capacities for total output of sector i in quarter t estimated by constructing i t of production function. 3

4 As it follows from equations above the current version of the model is mainly demandside. More updates for production capacity constraints and other supply-side equations will be presented at the next conferences. Notwithstanding this equilibrium variables of aggregated markets in equations (2) make the model GE type by harmonizing equilibriums of different aggregated markets. Table 1 Elasticity coefficients of total demand for product of sector i to real exchange rate, real wage, and real interest rate for main sectors of the Russian Economy (in parentheses time lags are specified, in quarters) Real exchange rate (Rub in USD) Real wage Real interest rate R 2 Agriculture -0,06 (1) -0,19 (3) 0,20 Coal 0,95 (0) -0,58 (0) 1,16 (0) 0,63 Oil 0,26 (0) 0,30 (0) 0,17 Natural Gas -0,44 (4) 0,53 (0) -0,28 (0) 0,78 Other minerals -0,25 (4) -0,54 (0) 0,30 Food, beverages, etc. -0,10 (4) 0,41 (0) 0,63 Clothes -0,30 (4) 0,51 (0) -0,26 (0) 0,65 Pulp industry -0,31 (4) -0,07 (0) -0,58 (0) 0,83 Oil refinery -0,20 (0) 0,25 Chemistry industry -0,39 (4) -0,06 (2) -0,60 (0) 0,61 Construction materials -0,30 (4) 1,20 (0) -0,67 (0) 0,79 Ferrous metallurgy -1,10 (3) 0,36 (0) -0,96 (3) 0,81 Non-ferrous metallurgy -0,27 (4) 0,46 (0) -0,47 (0) 0,68 Metal products -0,45 (4) 0,46 (0) -0,50 (0) 0,65 Machinery -0,57 (4) 0,79 (0) -1,43 (0) 0,62 Other industrial products -0,11 (4) -0,56 (0) 0,71 Energy -0,13 (4) -0,34 (0) 0,49 Water supply -0,13 (4) -0,34 (0) 0,49 Construction 0,15 (4) 0,75 (0) -0,75 (0) 0,61 Trade 0,06 (3) 0,67 (0) -0,43 (0) 0,92 Transport 0,41 (0) -0,40 (1) 0,53 Communication 0,41 (0) -0,40 (1) 0,53 Finance and Insurance -0,27 (2) 1,28 (0) -1,08 (2) 0,86 Real Estate and Consulting -0,30 (1) 1,02 (0) -0,79 (1) 0,62 R&D 0,08 (4) 0,47 (0) -0,20 (0) 0,76 Education 0,14 (0) 0,59 Health, Culture, etc. 0,08 (0) 0,41 Utilities 0,06 (4) 0,30 (0) -0,33 (0) 0,78 Empty fields means absence of statistically significant estimations (level of significance is 10% or more) Sources: Author s estimations based on official statistics for the Russian economy in To get estimations of the model parameters we ve estimated a technological matrix {a i,j } i,j = 1,, n for year 2010 and elasticity matrix {e i,k } i = 1,, n;k є {0; ExR$R; WR; IRR} by constructing multiple regressions using quarterly statistics of Russia in (see Table 1). The period was chosen for estimation because of two reasons. Firstly the Russian economy s 4

5 development met in in the main with demand constraints what has good correspondence with demand-side type of the model. In the second place, the Russian national accounts had been transited for a new classification of economic sectors from 2003, as a result sectoral data before 2003 are not comparable with data after Estimations given in Table 3 could be interpreted as estimations of competitiveness of sectors to deterioration of conditions on corresponding aggregated market. It allows us to use the theory of inter-sector competition to interpret the results of calculations in the model and to explain changes in the structure of the Russian economy. To construct model for aggregated money market we use well-known Baumol-Tobin model to simulate money demand and new-keynesian concept of inflation based on adaptive learning. In a model of inflation we assume that inflation expectation include non-monetary factors. Based on quarterly statistics for we ve estimated two following regressions: Ln((1+IRN t )/(1+IRN t-4 )) = 0,02+0,16*Ln(P t-4 /P t-8 ) 0,08*Ln( (M t /P t ) / (M t-4 /P t-4 ) ) + 0,16*Ln(X t-5 /X t-9 ) (R 2 = 80,2%) (4) Ln(P t /P t-4 ) = 0,146*Ln(M t /M t-4 ) + 0,979*Ln(P t-1 /P t-5 ) 0,321*Ln(P t-2 /P t-6 ) (R 2 = 67,1%) (5) where IRN t average annual interest rate for 1year or less credits for non-financial sector in quarter t; P t GO deflator index in quarter t; M t money supply (М2) in quarter t; X t real GO in quarter t. The model for money market allows to endogenize interest rate and inflation rate, and as a result endogenize links between aggregated money market and product market. Money supply is the only exogenous variable in this case. A model of currency market is based on estimation of currency inflows and outflows in the Russian Balance of payments and allows to simulate dynamic of exchange rate of the Russian ruble to USD. Based on quarterly statistics for we ve estimated following regression: Ln(ExR$N t /ExR$N t-4 ) = 0,04+1,20*Ln(1+dPrivateReserves t /CurrenceInflows t ) 0,49*Ln(1+dCurrenceInflows t /CurrenceInflows t ) (R 2 = 79,5%) (6) where ExR$N t average exchange rate of the Russian ruble to USD in quarter t; dprivatereserves t /CurrenceInflows t ratio of change in net foreign currency reserves of private sector to total foreign currency inflows in the Russian economy in quarter t; dcurrenceinflows t /CurrenceInflows t ratio of net foreign currency inflows in the Russian economy to total foreign currency inflows in the Russian economy in quarter t. To make exchange rate endogenous regression for import of goods and services (7) and normative model for export of goods and services (8) are constructed: Ln(1+Im t /P t *X t ) = 0, ,025*Ln(ExRR t /ExRR t-4 ) (PV = 99,7%) (7) Ex t = ExNonO&G t + OilPrice t *ExpOilVol t /doil t (8) 5

6 where ExRR t real exchange rate of Russian ruble to USD. Im t volume of import of goods and services in rubles in quarter t; Ex t volume of export of goods and services in rubles in quarter t; ExNonO&G t volume of non oil&gas export of goods and services in rubles in quarter t; OilPrice t average actual export price of the Russian oil in USD per barrel in quarter t; ExpOilVol t volume of oil export in barrels in quarter t; doil t average share of oil export in total oil&gas export in quarter t. Flows of capital and financial instruments accounts of Balance of payments and non oil&gas export of goods and services are exogenous. For purpose of macroeconomic forecasting this flows are defined exogenously according to considered scenarios of economic development and macroeconomic policy, retrospectives and expert estimations. The regressions above have a good correspondence with theoretical framework as well as statistical tests shows a good significant level for main statistical hypotheses. 2. Scenarios of forecast of the Russian economy development in with different scenarios of monetary policy The macroeconometric GE-IO model of the Russian economy with aggregated money and currency markets presented above allows to estimate influence of changing in monetary policy on the dynamics and structure of the Russian economy. Transition of the Russian Central Bank to the inflation targeting to suppress inflation rate to 4% in 2015 in conditions of slowdown in economic growth makes this issue to be very relevant. For example, according to our estimates 1 percentage growth of real interest rates has as a result 0.39% decreasing of GDP growth rates and 1.05% decreasing of Investments in fixed capital growth rates is a basis year for our calculations. Calculation for the period is the simulating the Russian economy with actual values of all parameters of the model except total output growth rates is a forecasting period. To ensure comparability of the results of calculations for different scenarios of monetary policy we construct base variant of forecast for The key assumptions for base variant of forecast for are as follows. 1. Annual growth rate of actual export prices of the Russian oil is 2%. 2. Annual growth rate of real wages in 2013 is 5.5%, in %. 3. Annual growth rate of GDP deflator of USA is 1.5%. 4. Annual growth rate of volume of non oil&gas export is 5.1% in USD. 5. Share of crude oil in total oil&gas export is 52.2%. 6. Annual growth rate of oil&gas extraction is 1.0%. 7. Net outflows of capital from Russia will increase from 72.4 bln USD in 2013 upto 79.8 bln USD in Simulating of inflation rates is based only on assuming of monetary factors and adaptive learning. A role of non-monetary measures of suppressing inflation is out consideration. The base variant of forecast do not take into consideration impact of anti-russia sanctions and Ukraine s crisis on the Russian Economy. Three scenarios of the Russian Economy development in are considered to estimate an impact of the squeezing of money supply. In the first scenario Inflation targeting it is suggested that annual inflation rates will be suppressed to 4.0% in The second scenario Neutral policy assumes that Central bank of Russia would not intrude in money market to 6

7 decrease inflation. The third scenario Monetary easing implies high growth rates of money supply to stimulate the Russian economy. All three scenarios are suggested similar dynamics of oil prices and real wages to carry ceteris paribus comparative analysis. The first two scenarios suggest endogeneity of money supply, which depends from the Russian Central bank s inflation targets, inflation rates are exogenous. The third scenario suggests endogeneity of inflation rates and exogeneity of money supply. 3. Results of calculation: influence of monetary shocks on the Russian economy in The results of calculation are presented in the Table 2. Data given in the Table 2 show that gradual transition to inflation targeting in Russia in had led to significant growth in real interest rates from -4.4% in 2011 to 2.5% in 2012 and 4.5% in To achieve 4.0% inflation rate in 2015 Central bank of Russia should decrease change rate of money supply from 11.9% in 2012 to only 0.9% in As a result there would be a sharp decrease in real GDP growth rates from 3.4% in 2012 to 1.0% in Fixed capital producers and capital investments get the most negative impact from the inflation targeting. Average annual change rate of capital investments would be -3.1% in this scenario. The main reason of this is significant growth in real interest rates from 2.5% in 2012 to 5.6% in According to the results of calculations the inflation targeting policy leads to significant fall in growth rates of the Russian GDP in approximately 1.3% in comparison to Neutral policy scenario. It causes raising real GDP losses from 0.9% in 2013 to 4.0% in 2015 in relation to Neutral policy scenario (see Fig. 1). Total real GDP losses in are equal to 7.2% of GDP in ,0 7,0 6,0 5,0 4,0 4,0 3,0 2,0 1,0 0,0 2,3 0,9 3,4 2,4 1, Change rate of the Russian real GDP in Inflation targetting scenario, % to the Russian GDP in 2012 the Russian real GDP losses in Inflation targetting scenario in according to Neutral policy scenario, % to the Russian GDP in 2012 Figure 1. Estimation of GDP losses from the inflation targeting in Russia in Sources: results of calculations 7

8 Dynamics of some key macroeconomic indicators of the Russian economy in Actual data Forecast Table 2 1 st scenario Inflation targeting 2 nd scenario Neutral policy 3 rd scenario Monetary easing Average export price of the 74,1 101,7 103,1 99,6 101,6 103,7 99,6 101,6 103,7 99,6 101,6 103,7 Russian oil, USD per barrel 31,1 22,3 11,9 14,6 10,0 6,8 20,7 20,1 20,0 30,0 30,0 30,0 Money supply change rate, % 4,5 4,3 3,4 1,4 0,9 1,0 2,4 2,3 2,5 3,2 3,8 4,4 GDP change rate, % Capital investments change rate, 6,3 10,8 6,6-2,2-3,7-3,6 0,4-0,2 0,5 2,6 3,8 5,1 % Average nominal exchange rate, 30,4 29,4 31,1 31,8 32,5 33,3 32,0 33,2 34,8 32,4 34,4 37,4 Russian rubles per USD 14,2 15,9 7,5 6,4 5,6 4,0 7,2 9,1 9,0 8,3 13,6 13,8 GDP deflator change rate, % Average annual nominal interest 13,4 10,4 11,2 11,4 11,3 9,8 9,6 11,3 10,9 8,4 11,6 10,4 rate, % Average annual real interest rate, -0,4-4,4 2,5 4,5 5,4 5,6 2,2 2,0 1,7 0,1-1,8-2,8 % Sources: Rosstat, Central bank of Russia; results of calculation in GE-IO model of the Russian economy with aggregated money and currency markets 8

9 The results of calculations allow us to conclude that the inflation targeting policy would be suitable for the Russian economy only in condition of high investing activity. But in the current conditions in the Russian economy characterized by an extremely low investment activity and technological backwardness it would be cause too large GDP losses and decline in capital investments. Thus, the obtained results substantiate the inconsistency of the existing model of macroeconomic policy in Russia with monetary-oriented suppression of inflation and structural policy aimed at modernizing and stimulating innovation. According to the results of our calculations macroeconomic policy s shocks have significant impact on development and structure of the Russian economy in current conditions. The most significant impact is related to monetary shocks. For example, the easing of a monetary policy by the increasing of annual growth rates of money supply from 20% to 30% lead to increase annual growth rates of the Russian economy in short-term period from % to % relatively. The estimates of impact of fiscal policy received by simulation in the present version of GE-IO model show restricted influence of its indiscriminate measures. In the same time specific measures of fiscal policy applied for certain sectors have a significant influence on dynamics of some processing industries and constructing. However the present version of the model has some restriction for apply to detailed consideration dynamic aspects of influence of macroeconomic policy on branch outputs. We plan to solve this in our further studies. 4. Some estimates of influence of fiscal shocks on the Russian economy The current version of the model used for estimation of the influence of monetary shocks in this study has not developed enough to get full insight on the consequences of fiscal shocks for the Russian economy. For this purpose it needs development and incorporating of the multisectoral model of state budget, reproduction of fixed capital, etc into the general model according to scheme 1, that has been planned at the next stages of the study. Nevertheless we can use this model to get some preliminary estimates of direct short-term effects of changing in the Russian fiscal policy. More updates will be presented in our following papers. Two following fiscal instruments are under our consideration in this paper: subsidizing interest rates of bank loans and growth of government purchasing of goods and services. Subsidizing interest rates of bank loans To get estimation of effects of subsidizing interest rates of bank loans we simulate Scenario Inflation targeting for 2013 with decreasing calculated annual nominal interest rate at 1 percentage point. As a result of simulation growth rate of GDP in constant prices in 2013 rises from 1.45% to 1.85% in this Scenario, that is equal additional growth of GDP at bln rubles in current prices. We also can estimate about 67.8 bln rubles of additional budget income in 2013 due to growth of fiscal base and accelerating of the Economy as a result of the subsidizing 2. To estimate additional expenditures of the state budget for this policy we use statistics of the Central Bank of Russia. According official data total volume of loans to organizations and householders by the Russian bank system is bln rubles in It allows to get a rude estimation of state expenditures for subsidizing at the level of 450 bln rubles. So even we take into account only bank loans to organizations and householders approved by the Russian bank system the pressure on the state budget in this policy would grow at least at bln rubles but seems to be 2 Additional budget income is calculated by multiplying of a ratio budget income to GO in 2013 (20.8%) and additional growth of GO due to subsidizing ( bln rubles). 9

10 much more. Considering loans from abroad and issued bonds in 2013 we have to conclude that the policy of subsidizing of should be applied very selective and aimed only at investment activity. The additional investigations are required to get appropriate estimations. Growth of government purchasing of goods and services To estimate impact of growth of government spending of goods and services to dynamic of the Russian real GDP we use official data for components of GDP by expenditure in Correcting estimation of the Russian GDP on changes in inventories and statistic errors we obtain the following results as shown in Figures 2 and 3. 25,0 20,0 20,6 16,7 15,0 10,0 5,0 5,5 8,0 9,1 11,1 11,9 9,9 5,3 6,0 1,9 2,0 1,3 3,2 0,9 1,4 3,6 0, ,4-5,0 Consumption Export Investment Government spending Import GDP corrected* Figure 2. Average annual change rates of the Russian GDP (corrected) and its components, in percent 150,0 122,0 100,0 50,0 0,0 71,2 72,6 55,0 33,5 37,6 28,8 21,4 24,4 6,9 6, ,1-50,0-66,5-45,8-62,6-100,0 Consumption Export Investment Government spending Import Figure 3. Contribution of the components of GDP to average annual change rates of the Russian real GDP (corrected), as a share, in percent 10

11 The assessment of effect of growth of government purchasing of goods and services is based on the concept of full costs in the Leontief model (see Table 3). Table 3 Estimations of full cost coefficients for main sectors of the Russian economy in constant prices of 2010 Approximate direct budget income effect to 1 ruble of Full costs expenditures* Agriculture 2,041 0,425 Coal 2,165 0,451 Oil 1,387 0,289 Natural Gas 1,554 0,324 Other minerals 2,033 0,424 Food, beverages, etc. 2,605 0,543 Clothes 2,778 0,579 Pulp industry 2,426 0,505 Oil refinery 1,859 0,387 Chemistry industry 2,752 0,573 Construction materials 2,331 0,486 Ferrous metallurgy 2,511 0,523 Non-ferrous metallurgy 2,304 0,480 Metal products 2,820 0,588 Machinery 2,597 0,541 Other industrial products 2,636 0,549 Energy 1,899 0,396 Water supply 1,939 0,404 Construction 2,290 0,477 Trade 1,731 0,361 Transport 1,911 0,398 Communication 2,623 0,546 Finance and Insurance 1,612 0,336 Real Estate and Consulting 2,303 0,480 R&D 2,061 0,429 Education 1,544 0,322 Health, Culture, etc. 1,592 0,332 Utilities 1,810 0,377 * Estimations are based on the ratio of budget income to GO of Russia in 2013 and needs to refine with detailed multisectoral model of state budget. More updates will be presented during the 22 nd World INFORUM Conference. 5. Aggregated macroeconometric GE model To assess macroeconomic effects influenced by monetary and fiscal policy in we refine our estimates for change rate of GDP s deflator in quarter t to the same quarter of the previous year (π t, in percent), annual nominal interest rates (R t, in percent), and construct an equation for the real GDP change rates (y t, in quarter t to the same quarter of the previous year, in percent): 11

12 2 ˆ π t = 0, ,765 π t 1 + 0,118 mt + 0,608 ( yt yt ), R = 0,79 ˆ 2 Rt = 0, ,773 Rt 1 + 0,077 π t 1 0,038 mt + 0,139 yt 3, R = 0,94 2 yˆ t = 0,344 0,064 rert 4 + 0,499 rwt 0,384 ( Rt π t ) + 0,516 et 1, R = 0,94 where m t change rate of money supply M2 in quarter t to the same quarter of the previous year, in percent; rer t change rate of real exchange rate of the Russian ruble to USD in quarter t to the same quarter of the previous year, in percent; rw t change rate of real wages in quarter t to the same quarter of the previous year, in percent; e t deviation of actual change rate of real GDP in quarter t to the same quarter of the previous year from calculated. These three equations form the aggregated macroeconometric GE model of the Russian economy, which based on the same assumptions as the GE-IO model described before. The aggregated model allows to estimate contribution of fiscal and monetary shocks to dynamics of real GDP of the Russian Federation in (see Figures 4 and 5, respectively, and Figure 6 for combined effects). 3,0 1 2,5 2,0 1,5 1,0 0,5 0, ,5-1,0-1,5 Figure 4. Contribution of fiscal shocks* to change rates of real GDP of the Russian Federation in , in percent to the same quarter of the previous year * related only with changes in real wages in state sector and government spending 12

13 5,00 4,00 3,00 2,00 1,00 0, ,00-2,00-3,00-4,00-5,00 Figure 5. Contribution of monetary shocks* to change rates of real GDP of the Russian Federation in , in percent to the same quarter of the previous year * as changes in money supply M2 annual growth rates 8,0 6,0 4,0 2,0 0, ,0-4,0-6,0-8,0-10,0-12,0 Fiscal policy effect Monetary policy effect Actual GDP change rates Fiscal and monetary policy effects Figure 6. Contribution of fiscal and monetary shocks to change rates of real GDP and dynamics of real GDP of the Russian Federation in , in percent to the same quarter of the previous year 6. Conclusion The above applications of the macroeconometric general equilibrium input-output model of the Russian economy with aggregated money and currency markets and its aggregated version for estimation of effects of macroeconomic policy show high relevance and usefulness. Considering of situation at aggregated markets and macroeconomic shocks in the model allows 13

14 to simulate different scenarios of macroeconomic policy and obtain estimations for policy making. But the presented version of the model is very simple and requires more extension, especially in incorporating of the multisectoral model of state budget and model of reproduction of fixed capital into the general model according to scheme 1. Bibliography 1. Central Bank of the Russian Federation. The main directions of state monetary policy in 2013 and in Baranov A.O. A slowdown of economic growth in Russia and prospects of overcoming it // EKO p Gilmundinov V.M. Estimation of influence money and currency markets parameters on productivity of the Russian economy // Vestnik of Novosibirsk state university. Social and economic sciences series T. 12, 1. - p Clopper Almon, The Craft of Economic modeling, 2nd edition, Needham Heights, MA, Ginn Press, Leif Johansen, A Multi-Sectoral Study of Economic Growth, 2nd enlarged edition, Amsterdam, North Holland Publishing Company, Monetary policy, inflation, and the business cycle: an introduction to the New Keynesian framework / Jordi Gali New Jersey: Princeton University Press,